FedCSD: A Federated Learning Based Approach for Code-Smell Detection

Software quality is critical, as low quality, or "Code smell," increases technical debt and maintenance costs. There is a timely need for a collaborative model that detects and manages code smells by learning from diverse and distributed data sources while respecting privacy and providing...

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Bibliographic Details
Published in:	IEEE access Vol. 12; p. 1
Main Authors:	Alawadi, Sadi, Alkharabsheh, Khalid, Alkhabbas, Fahed, Kebande, Victor R., Awaysheh, Feras M., Palomba, Fabio, Awad, Mohammed
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.01.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Accuracy Application programs Code Code smell Code Smell Detection Codes Codes (symbols) Companies Computer software maintenance Computer software selection and evaluation Costs Cryptography Data privacy Datasets Experiments Federated learning Ho-momorphic encryptions Homomorphic encryption Homomorphic-encryptions Maintenance costs Maintenance engineering Model accuracy Object oriented modeling Object oriented modelling Object oriented programming Odors Privacy Privacy preserving Quality management Software development Software engineering Software quality Source code Technical Debit Training
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
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